As the baby boomer generation ages, the number of hip replacement surgeries is expected to increase. In 2001, about 165,000 hip joints were replaced in U.S. hospitals according to the National Center for Health Statistics, and 326,000 knees were replaced. While the majority of joint replacement patients remain in the 60-plus year category, more people are deciding to have surgery one or two decades earlier.
About 70 percent of people seeking hip replacement surgery have severe osteoarthritis, a common chronic disease that damages cartilage, the tissue that acts as a protective cushion allowing for the smooth, low-friction movement of the joint. Osteoarthritis is the leading cause of long-term knee damage and the most common reason for knee replacement. By age 65, women are five times more likely than men to have this disease.
A common goal for physicians when replacing joints is to minimize the discomfort and the recovery time, and reduce the time it takes to successfully install the joint implant while properly installing the new joint to provide the best possible range of motion for the patient using materials and techniques which will maximize the lifetime of the replacement joint. To this end, pre-surgery modeling is an important step in the joint replacement process so that the surgeon is able to properly select the best joint replacement option and estimate how it will be implanted, move, and affect the patient prior to the actual surgery.
Unfortunately, many current pre-operation techniques only focus on selecting a prosthesis which will fit static two-dimensional requirements based on acetate portrayals of a prosthesis which are then overlaid on a two-dimensional x-ray. For example, for hip replacements, current planning for acetabular implant placement and size selection is performed using acetate templates and a single anterior-posterior X-Ray of the pelvis. Acetabular templating is most commonly performed to determine the approximate size of the acetabular component, but there is little effort to accurately determine the ideal position of the implant or the effect such placement will have on the patient.
Without accurate modeling, physicians may face uncertainty in the actual operation when deciding where to remove existing bone and/or tissue as well as how much to remove. Such uncertainty raises risks with inexperienced physicians and can also keep experienced physicians from using newer and improved joint replacement options since they are more sure of the operation experience with older technology.
Therefore, there is still a need for methods and systems which more accurately enable physicians to model surgical joint replacement.